Environmental Consequences of the Kakhovka H.P.P. Destruction in Ukraine: Challenge and Opportunity for International Justice
Bibliographic record
Abstract
This article provides a legal analysis of the destruction of the Kakhovka hydroelectric power plant dam that took place on June 6, 2023 in Russian-occupied Ukraine. Highlighting the role of Russian troops in this act, the authors equate its consequences to the 1986 Chornobyl disaster. The dam's explosion marks a severe environmental catastrophe amidst ongoing high-intensity hostilities in Ukraine, threatening vast natural areas with environmental disaster. Authors discuss the broad environmental and cross-border impacts, particularly in the Black Sea basin, and review the international environmental conventions breached by this incident. The event aligns with the concept of ecocide, a term not yet fully established in international law, but increasingly recognized. The article emphasizes the possibility of prosecuting those responsible for extensive, long-term, and severe environmental damage under existing legal frameworks. Focusing on international legal instruments, the article explores the grounds for international criminal responsibility and examines the jurisdictions that could address the ecocide, including the International Court of Justice, the International Tribunal for the Law of the Sea, a proposed Special Ad-Hoc Tribunal, and the International Criminal Court (ICC). The authors argue that the Kakhovka dam case presents the ICC with a unique opportunity to enforce international norms against severe environmental damage during hostilities, as outlined in Article 8.2b (iv) of the Rome Statute. They conclude that the ICC’s involvement would be a significant step in proving its capability to address war crimes involving environmental destruction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".